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Release Notes - Version 1.7.2

Release Date: October 4, 2025
Type: Feature Release

Overview​

Version 1.7.2 introduces Near-Infrared (NIR) augmentation capability, enabling vegetation analysis, NDVI calculation, and enhanced multi-modal machine learning datasets.

🌿 What's New​

Infrared Augmentation​

Add Near-Infrared values from IGN IRC orthophotos to your LiDAR point clouds:

  • NIR Integration: Fetch and integrate infrared data from IGN GĂ©oplateforme WMS service
  • NDVI Ready: Calculate vegetation indices (NDVI, EVI, GNDVI, SAVI) directly from enriched tiles
  • Multi-Modal Datasets: Combine Geometry + RGB + NIR for superior machine learning models
  • Smart Caching: Efficient disk and GPU caching system (shared with RGB augmentation)
  • Seamless Integration: Works alongside RGB augmentation in the enrich pipeline

CLI Integration​

# Enrich with infrared
ign-lidar-hd enrich --input tiles/ --output enriched/ --add-infrared

# Combined RGB + Infrared (recommended)
ign-lidar-hd enrich --input tiles/ --output enriched/ \
  --add-rgb --add-infrared \
  --rgb-cache-dir cache/rgb \
  --infrared-cache-dir cache/infrared

# Full-featured processing
ign-lidar-hd enrich --input tiles/ --output enriched/ \
  --mode full --auto-params --preprocess \
  --add-rgb --add-infrared \
  --use-gpu

Pipeline Configuration (YAML)​

enrich:
  mode: full
  add_rgb: true
  rgb_cache_dir: "cache/rgb"

  # New: Infrared augmentation
  add_infrared: true
  infrared_cache_dir: "cache/infrared"

Python API​

from ign_lidar.infrared_augmentation import IGNInfraredFetcher
import numpy as np

# Initialize fetcher
fetcher = IGNInfraredFetcher(cache_dir="cache/infrared/")

# Augment points with NIR values
nir_values = fetcher.augment_points_with_infrared(points)

# Calculate NDVI
ndvi = (nir - red) / (nir + red + 1e-8)

Output Format​

  • Extra Dimension: NIR values stored as 'nir' extra dimension (uint8, 0-255)
  • LAZ 1.4 Compatibility: Standard LAZ format with extra dimensions
  • CloudCompare Support: View NIR values as scalar fields

Bug Fixes​

  • Fixed metadata copying for single-file input (issue with relative path calculation)
  • Enhanced COPC format handling and conversion
  • Improved error handling for WMS service requests

Documentation Updates​

  • Added comprehensive Infrared Augmentation Guide
  • NDVI calculation examples and use cases
  • CloudCompare visualization guide for NIR field
  • Updated all example configurations with infrared settings
  • Enhanced French and English documentation

Breaking Changes​

None

Installation​

Update to the latest version using:

pip install --upgrade ign-lidar-hd==1.7.2

Compatibility​

  • Python 3.8+
  • All existing APIs remain compatible

Contributors​

  • Simon Ducournau

For complete documentation, visit our documentation site.